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Rev AI Fusion (Whisper Fusion)

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Rev AI Fusion (Whisper Fusion) is a closed-weights speech-to-text model from Rev, released January 2024. Licence: proprietary.

Catalogue identity notes

Rev AI async API transcriber='fusion' (Whisper Fusion; added 2024-01 per Rev's changelog). Rev deprecated the fusion option on 2026-08-20, so api is null.

56.5±3.7comparison only: no current run option verifiedfrom 2 benchmark results across 1 source* thinly tested, treat the rank as provisional

Score within the Open ASR English short-form WER (March 2026) comparison set only.

$ how it compares

The speech-to-text models ranked either side of Rev AI Fusion (Whisper Fusion), out of 176 with a score, then more from Rev.

#modelscorewhereRAMreleased
68GLM-ASR-Nano-2512 Z.ai57±4local~5.9GB2025-12
69Parakeet RNNT 0.6B NVIDIA57±3local~3.5GB2024-01
70Rev AI Fusion (Whisper Fusion) Rev57±4comparison only2024-01
71Orukeet Oruk AI57±4local~0.7GB2026-09
72Zipformer Transducer XL 290M SoundsGood AI56±5comparison only2026-05
more from Rev
100Rev AI Machine (Reverb ASR) Rev52±3api $0.0033/audio min

see all speech-to-text models · find the ones that fit your machine

$ what it's good at

long-form transcription▁▁▅▁·▃▅█▆▁▂▂ #6 of 31 * · 47% of its score · 1 test

Beats Canary-Qwen-2.5B, Chirp 3, Parakeet TDT 0.6B v2 here, though they rank higher overall.

testresultvs the others in its rundifficultycountswhy
Open ASR English long-form WER8.5% ✎▁▁▅▁·▃▅█▆▁▂▂ beats 25/30avg 12%▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 47%typical
other tests1 not in a task · 47% of its score
testresultvs the others in its rundifficultycountswhy
Open ASR English short-form WER (March 2026)7.1% ✎▁▁▁▃··▁▁▂██▆ beats 57/86avg 8.2%▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 47%blunt

$ where to run it

No verified API or download recorded yet · add one

$ how the score was worked out · Open ASR Leaderboard 95%

Each result implies a score on its own, after adjusting for how hard its test is and who ran it. The score is their weighted average, with a small pull toward the middle for thinly tested models. Each test's weight is its counts column above; here it's added up by who ran the tests. How it works

sourceresultsshare of the scorelicence
Open ASR Leaderboard2▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 95%Apache-2.0
prior · pull toward the middle▇▇ 5%
weighted average= 56.5

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data updated · sources and licences · json